Gradient compute fail when using RawFeatureVector

[saalimon]

Information

• Qiskit Machine Learning version: 0.1.0
• Python version: 3.7.10
• Operating system: All

What is the current behavior?

This message occurs when using RawFeatureVector with CircuitStateFn
Cannot compute gradient operator! Continuing without gradients!

Steps to reproduce the problem

from qiskit import QuantumCircuit
from qiskit.opflow import StateFn, PauliSumOp, AerPauliExpectation, Gradient
from qiskit.utils import QuantumInstance
from qiskit_machine_learning.neural_networks import OpflowQNN
from qiskit_machine_learning.circuit.library import RawFeatureVector

expval = AerPauliExpectation()
gradient = Gradient()
qi_sv = QuantumInstance(Aer.get_backend('statevector_simulator'))

inputs = RawFeatureVector(16)
qc = QuantumCircuit(4)
qc.append(inputs,range(4))
qc_sfn = StateFn(qc)
H1 = StateFn(PauliSumOp.from_list([('Z', 1.0)]))
op = ~H1 @ qc_sfn
qnn4 = OpflowQNN(operator = op, input_params = inputs.parameter, weight_params = [], exp_val = expval, gradient = gradient, quantum_instance = qi_sv)

What is the expected behavior?

Can pass the Parameter or ParameterVector to OpflowQNN or another Opflow from qiskit_machine_learning.neural_networks

Suggested solutions

Check the Gradient condition on qiskit.opflow

[ElePT]

Hello! I would like to work on this issue.

[adekusar-drl]

Closed in #182.